Yet Another Method Of Ranking Teams

Intro

An idea has been nagging me for the last few weeks that goes like this: to say a team's goal is to win the game is needlessly over-specific. Any rational team’s goal is to have the lead all game. So every second you don’t have the lead is a failure to some degree. Not only that, but a measurable failure.

With this in mind, I was surprised that none of the computerized rankings sound like they take lead time into account. Sagarin, Massey, Colley, Wolfe and Harris don’t mention it on their sites. This fed my curiosity of whether it’s any good as a metric. For the record, I didn't seek out to prove anything. Most of all, I just wanted to take a look at the season through a different lens. With that said, onto the…

Data

I started with the 2012 per-drive data from cfbstats.com (H/T to mgousesr TSS for pointing me there), then calculated lead times in each game. Then I weighted those leads against the strength of the team the lead was against. I used my own results from the first calculation for the team strength metric, so that my results were not skewed in the slightest by anyone else’s formula. Then I weighted those results one more time for good measure, so opponents’ opponents are weighed in. The only factor considered is amount of time teams had the lead in games.

Charts

The Norm 1 (or normalized 1 time) ratings rank teams based on the amount of time they had a lead this season, nothing else. Norm 2 weights lead times against the Norm 1 rating of the opponent. Norm 3 weights lead times against the Norm 2 rating of the opponent.

The list, in three parts:

Top teams in graph form:

Some important notes with the data and/or formula

No 2-pt conversions or missed extra points are accounted for because the data I used doesn’t mention them. All touchdowns are assumed to be 7 points.

After calculating the running score in games, some of the outcomes of games were...off. Just a little bit. This is probably because of the last bullet.

Tie scores are ignored. I think it might be worth it to value them somehow, but I didn’t have time.

Because of the last caveat, a constantly tied slugfest is worth less than a back and forth game. This should only affect the kinds of teams that get into these kinds of games, i.e. the middling ones, but it still bothers me.

To add to the last point, I therefore believe the very best and very worst teams are ranked the most accurately

Overtime is ignored

Even with team weightings, you are rewarded slightly more for leading the whole game against #19 Utah State than for leading for half of the game against #1 Alabama.

You are rewarded more for giving away a game where you led all the way than for being on the other side of that.

Injuries that affect today’s team are not factored into yesterday’s results.

A strategy to wear other teams out may arguably be lead-agnostic early in the game. However, Oregon and Alabama are the kings of this strategy—in radically opposite ways no less—and they are the top two teams rated. So there’s that.

But anyway, onto…

Analysis

Well, the results are unique, that's for sure. But they're not exactly out of left field, either. And some of them are downright acceptable.

Surprise Bullets

Michigan: I have to admit, part of the reason I did this was to prove that Michigan is better than their record. This may still be true, but not according to my formula. Why would this be? It's simple, really. I've given them a lot of credit for playing top teams, but they rarely led in these games. Deep down, what's the difference between losing all game and never showing up? In regards to the Alabama game I can say not much. Furthermore, their most dominant performances came against the worst opponents on their schedule. That shouldn't be a surprise, but if it’s true, neither should the fact that they are properly rated. I am disappoint.

Oklahoma State: A 7-5 team that was competitive in every loss but one is my #6 team. I wonder if their fans and MSU’s fans have a support group, and if so, where would they find a couch.

Ole Miss: I barely noticed this team this year. I wonder how their fans feel about their season. They were 6-6 but they may be in for a bounce next year if nobody leaves.

Utah State: Holy crap did they ever have an under the radar season. But they do drop from #4 to #19 once you factor strength of schedule. Let’s not play these guys, you guys.

Not Surprise Bullets

Notre Dame is not the best team but they are good. They look better when the strength of opponent is factored in (#4 vs #8).

Ohio State is not an elite team. That's probably partly why Michigan played them so close. Like Notre Dame, the strength of opponents they led against does bump them up quite a bit (from #26 to #13).

Texas A&M beating Alabama is somewhat less of a surprise—they’re my #3 team.

Florida is overrated, said everyone ever until they beat Florida State. But guess who else is overrated? Florida State (their line happens to be one of the most interesting ones, though).

Michigan State is...marginally better than Michigan? Well, no one would be surprised if you had claimed this in August.

Stanford beat Oregon, had a tougher schedule, and won the Pac 12. So why do a lot of people just assume that Oregon is the better team? These results might explain why. Oregon was actually a lot more dominant all season, all else being equal. I mean if you don’t count all the stuff that counts.

Takeaways

Proving my assumptions about Notre Dame and Ohio State almost offsets the disappointment in not proving my assumptions about Michigan.

The championship game should probably be Oregon-Alabama, just like a lot of people assumed for most of the season. Go BCS.

In a 4-team playoff, Notre Dame and their undefeated record would deserve a shot. As would Texas A&M, owners of the best win by any team all season.

These results would be considerably more controversial if Georgia had defeated Alabama, or Michigan had eked out a 2011-esque win against Notre Dame. But none of this happened and maybe there’s a lesson in that.

I do think that completely removing wins and losses from the equation takes a little of the fun out of it. And it leads to teams with 6 wins being rated higher than BCS juggernauts…like Northern Illinois. But on the other hand, I don’t see why this metric couldn’t be used in unison with a few others in determining how dominant of a season a team had.

Vegas, which you may know is in the business of predicting games, would no doubt give less than ten points to Bama against Oregon, the current line against Notre Dame. Hey, if Vegas agrees with my relatively simple formula more than the one the big boys use, maybe my poll is better.**

Phew, sorry for the long post. If anyone’s interested, I would consider running this against previous seasons, and hopefully writing a lot less. I would also consider tweaking the formula if the improvements are obvious and consistently better.

* I can’t think of a good name for this. “Lead metric”?

** for the record, Vegas does disagree with some of my rankings. For example, in the bowl games Vegas favors Miss State over Northwestern and Stanford over Wisconsin. Could be because the Big Ten sucked and I didn’t weight the data properly. Also, I already warned you about middling teams. Ctrl-F it.

Comment viewing options

...WOW...nice job on this diary. I truly love these sorts of posts...where the OP has a theory or inkling and sets about to prove/disprove with tons of DATA. Really well done, great writing/grammar and intelligent.

Here are some thoughts:

Obviously, WINNING is the most critical aspect of any ranking so to leave that out of your formula is probably what most people will harp on...howeva, I love where this is headed.

My suggestion would be to somehow weight the lead higher as the game progresses. For instance, having the lead at the end of the 4th Qtr is worth more than having the lead in the beginning of the 4th Qtr and having the lead in the 3rd Qtr is worth more than having the lead in the 2nd Qtr.

Another thought is to weight the margin of the lead. A 2 point lead is worth more than a 1 point lead, a 21pt lead is worth more than a 7pt lead, etc.

Finally, this was awesome, keep up the good work! GO BLUE!

Two roads diverged in a wood, and I—
I took the one less traveled by,
And that has made all the difference.

If you have a team that scores a touchdown in the 1st quarter, well that's fine and they may take the lead. But by the 4th quarter when that team scores another touchdown, they may be down by 21. So basically, yes, I agree with the above poster that the "leads" matter more by quarter after there is more data (e.g. more scores) from which to draw a conclusion.

If you did this, you would then take into account a lead at the end of the 4th quarter being the highest weight (aka a "win"), but it would not have to be that much higher than the 30 sec remaining mark in the 4th quarter. In other words, hail marries are awesome, but shouldn't destroy the ranking of the losing team as the odds are usually in the losing team's favor to win the game until, well, they don't.

I love the 1.0 version though so don't take this as a critique. It is awesome and great progress. Perhaps if there is a 2.0 ranking measurement, you can take this into account.

Why not just track the number of minutes a team is ahead, behind or tied?

Teams that dominate a game (e.g. 2012 Michigan versus Illinois 45-0) would have a brief period when the game was tied - in the case above, Michigan scored at 6 minutes into the 1st quarter and led the whole way.

So the result would be BEHIND: 0 minutes, TIED: 6 minutes, AHEAD: 54 minutes.

For a closer game (e.g.. 2012 MSU versus Michigan, 12-10)

No score in 1st quarter - TIED: 15

2nd quarter - Michigan scores FG at 10 mark, so that means the 5 min leading up the score were TIED: 5 min, AHEAD at 10 mark, added second FG at 1 min mark, so led for the remaining 10 min.

In the 4th quarter UM trails until in the 13th minute FG makes it 9-7, BEHIND: 7+2=9, TIED: 20, AHEAD 18 at this point, we stay ahead until MSU scores a FG at the 5 minute mark, making it 10-9, so we add 8 minutes to the AHEAD =18+8=26. We don't score until under the final minute FG, so rounding the full minute, we are behind 5 more minutes and ahead only 1. Final line:

BEHIND 14, TIED 20, AHEAD 27 (doesn't add up perfectly to 60 minutes due to rounding to next minute, didn't feel like adding up the seconds but it could be done). This is a classic close game: nearly evenly split between TIED, BEHIND, and AHEAD.

What about a game we snuck back to win? (Northwestern vs UM 2012 38-31 OT)

3rd quarter - Oregon scores at 6 min mark making it 14-7. They hold the lead through the end of the quater. For Standford: TIED: 35, AHEAD 9, BEHIND: 6

4th quarter - Stanford equalizes at the 1 minute mark. For Stanford: TIED: 36, AHEAD: 9, BEHIND: 20 (14+6) Score is 14-14 going to OT. Again I'm rounding up - ideally one could just use the actual number of seconds but I doing this on the fly and didn't dig out the spreadsheet.

Don't know what to call this stat - Time of Advantage, Time Ahead, Time of Dominance but it may be of value in assessing the nature of the wins and losses in an more objective way.

Easy to find data. Easy to understand and calculate. Offers insight into a game.

A 28-0 victory might have been for the winning team TIED:50, BEHIND: 0, AHEAD 10 when the other team finally wore out. In contrast a 35-0 blowout might have been a laugher from the start with a line of TIED: 1, BEHIND:0, AHEAD: 59. Yet in the paper, the two results might seem the same.

Interesting idea, and definitely a metric worth including in a more comprehensive evaluation, but I think you undervalue Ws. Being that I graduated in 1998 (i.e., with the 1997 NC team), I've always been a defender of teams who just know how to close out games. While dominating a game definitely gives insight into a team's strength, I don't think domination is any more valuable than having the skills, coaching, etc. to come back from a deficit to win a game that most teams would lose (see UM-Iowa, 1997). Clearly these are two opposite approaches to winning, but in the end, it's the W/L record that counts most.

Many of the points above are the initial suggestions that I formed, but are we "rationalizing" the improvements in an attempt to disprove Michigan's ranking? I concur with list - but It is tough to accept UM so far from ND and OSU.

It's also provides a scenario tool:
- Since we lost 2 games by <7 pts, I wonder how far Michigan would climb if we had 2 lucky plays in the last minute to win and how far ND and OSU would sink?
- Conversely, what if field goals were missed vs NU and MSU at the end?

a feeling we'll be seeing this as 'Diary of the Week'. Awesome job. A couple small things to mention:

You say you "didn't seek out to prove anything" but later say "part of the reason I did this was to prove that Michigan is better than their record." These are obviously contradictory. I'm not in the scientific or mathematics community, but is this some form of bias? I know all you are using are statistics from a third party, so there really shouldn't be, but is there a way to counter this? I mean other than not stating them lol.

Great job nonetheless. In fact forget about what I said I really don't know if this is a fallacy or not.

Doesn't this privilege success early in the game over success late in the game? Imagine team a dominates the first half and wins it 14-0. Team b dominates the second half to the same degree and wins 14-0. It seems like the teams had the same amount of success yet a led almost the whole game and b never led simply due to order